Data Engineer: Fabric Lakehouse & Real-Time Analytics

EXL Talent Acquisition Team; United States; Hybride; USD 94 000 - 145 000; Plein temps

Résumé du poste

Fabric Analytics is seeking a Data Engineer for a hybrid role based in Newark, NJ. The position focuses on designing and implementing end-to-end data solutions using Microsoft Fabric components, including Data Factory, Lakehouse, and OneLake, to support large-scale datasets across insurance-like domains.

The role involves creating scalable data models, reusable architectures, and efficient ingestion pipelines while optimizing performance and costs in Azure and Fabric environments.

Qualifications

• Architect and implement end-to-end data solutions across Fabric components.
• Design scalable data models and storage strategies for insurance-like datasets.
• Create blueprints and reusable frameworks aligned with enterprise standards.

Responsabilités

• Architect and implement end‑to‑end data solutions using Microsoft Fabric components including Data Factory, Lakehouse, Warehouse, Real‑Time Analytics, and OneLake.
• Design scalable data models, integration patterns, and storage strategies to support insurance datasets such as policy, claims, billing, actuarial, and customer information.
• Create architectural blueprints, reference architectures, and reusable frameworks that align with enterprise engineering and cloud standards.
• Develop and manage ingestion pipelines using Fabric Data Factory, enabling batch, real‑time streaming, and API‑based data integrations.
• Build Lakehouse‑centered architectures to support analytics, reporting, and machine learning workloads.
• Optimize data pipelines for performance, reliability, and cost across Azure and Fabric environments.

Outils

Microsoft Fabric Data Factory and Lakehouse

Real-Time Analytics

OneLake

Azure

Description du poste

Fabric Analytics is seeking a Data Engineer for a hybrid role based in Newark, NJ. The position focuses on designing and implementing end-to-end data solutions using Microsoft Fabric components, including Data Factory, Lakehouse, and OneLake, to support large-scale datasets across insurance-like domains.

The role involves creating scalable data models, reusable architectures, and efficient ingestion pipelines while optimizing performance and costs in Azure and Fabric environments.